JD:

- Experience in Credit Risk Modeling PD/LGD/EAD - TTC, PIT, Stressed and unstressed portfolio.

- Experience in Model Development, Model Validation, Model Audit

- Develop, validate, and document credit risk models (PD, LGD, EAD) for retail and wholesale portfolios across regulatory (CECL, IFRS 9, Basel)

- Apply AI/ML algorithms (e.g., LightGBM, XGBoost, Random Forest, Neural Networks) to improve prediction power and model performance beyond traditional approaches.

- Implement Generative AI and LLM-based applications using RAG pipelines, document intelligence, and model documentation automation. Experience with agentic frameworks like Autogen, LangChain, or similar would be helpful.

- Experience of development and deployment of models in cloud-based platforms such as Azure, AWS, GCP etc. in AI/ML or GenAI model development or validation.

- Strong understanding of credit risk modeling frameworks, scorecard development, and risk metrics (e.g., RWA, Expected Loss, Economic Capital).

- Proficient in Python and SQL, with hands-on experience using ML libraries such as scikit-learn, Tensorflow, Pytorch and transformer-based LLM packages

- Familiarity with regulatory standards such as CECL, IFRS 9, CCAR/DFAST, Basel II/III, SR 11-7, and model governance best practices.

- Exposure to cloud environments (Azure preferred), version control (Git), and workflow automation tools. experience with counterparty risk concepts (PFE,SA-CCR, EPE etc

- Leveraging experiential know-how of a wide range of financial products like Equity, Derivative, Swaps, IR, Credit derivatives, OTC products, Swaps, Securitization, CDO's etc.

- Knowledge of one or more of global regulatory Topics BASEL II/III, IFRS 9, CCAR/DFAST, CECL, FRTB, SR-11/7 around data sufficiency, modeling methods, industry standards etc.

- Possessing knowledge of Allowance for Credit Losses, including methodology, models, and US GAAP requirements under Current Expected Credit Losses (CECL) and knowledge of IFRS 9;

- Strong writing and communication skills across complex accounting, credit, and model topics

- Experience in the reserve, finance, or controllership organization at a large financial institution

- Experience in designing, building, and/or validating qualitative reserves for financial institutions across a broad array of asset classes, including both consumer and commercial loans.

Demonstrates a thorough level of abilities and/or a proven record of success with designing and implementing process improvement solutions, leveraging PC applications including MS Office (Word, Excel, Access, PowerPoint), where applicable, including:

- Knowledge of typical credit reserve methodologies used at financial institutions to determine the allowance for loan losses (i.e., Credit Reserve, ACL, or CECL).

- Operating successfully as both an individual contributor and team member, identifying and addressing client needs. Preparing, coordinating, and delivering complex written and verbal materials to clients and senior management (e.g., PPT presentations, summary reports/ memos, oral presentations);

- Collaborating with teams to create a proven atmosphere of trust, seeking diverse views to encourage improvement and innovation, and coaching staff, including providing timely meaningful written and verbal feedback;

- Identifying and addressing client needs by building and maintaining trust (e.g., client relationship management);

- Considering cross-cultural differences, seeking diverse views to encourage improvement and innovation, and fostering a global mindset for the team;